Cited by 115Reproductive Health and ContraceptionReproductive Health and TechnologiesMobile Health and mHealth Applications

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Can apps and calendar methods predict ovulation with accuracy?

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Johnson, Sarah, Marriott, Lorrae, Zinaman, Michael·2018·Current Medical Research and Opinion

DOI 10.1080/03007995.2018.1475348

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Abstract

OBJECTIVE: The accuracy of prediction of ovulation by cycle apps and published calendar methods was determined by comparing to true probability of ovulation. METHODS: A total of 949 volunteers collected urine samples for one entire menstrual cycle. Luteinizing hormone was measured to assign surge day, enabling probability of ovulation to be determined across different cycle lengths. Cycle-tracking apps were downloaded. As none provided their methodology, four published calendar-based methods were also examined: standard days, rhythm, alternative rhythm and simple calendar method. The volunteer ovulation data was applied to the app/calendar methods to determine their accuracy. RESULTS: Mean cycle length was 28 days (range: 23-35); 34% of women believed they had a 28-day cycle, but only 15% did. No LH surge was seen for 99 women. Most likely day of ovulation for a 28-day cycle was day 16 (21%). Accuracy of ovulation prediction was no better than 21% by the apps. The standard days and rhythm methods were most likely to predict ovulation (70% and 89%, respectively) but had very low accuracy. CONCLUSIONS: Ovulation day varies considerably for any given menstrual cycle length, thus it is not possible for calendar/app methods that use cycle-length information alone to accurately predict the day of ovulation. National Clinical Trial Code: NCT01577147. Registry website: www.clinicaltrials.gov .

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Authors: Johnson, S., Marriott, L., & Zinaman, M.
Affiliations: SPD Development Company Ltd, Clinical and Regulatory Affairs, Bedford, UK;
SPD Development Company Ltd, Statistics and Data Management, Bedford, UK;
Albert Einstein College of Medicine (US)
Corresponding author: Johnson, Sarah
ORCID: Johnson, Sarah
Marriott, Lorrae
Venue: Current Medical Research and Opinion
Publisher: Informa UK Limited
Published: 2018-05-25
Volume: 34
Issue: 9
Pages: 1587-1594
ISSN: 0300-7995 (ISSN-L)
1473-4877
DOI: 10.1080/03007995.2018.1475348
OpenAlex: W2801130706
Cited by: 115
References: 25
Citations by year: 2026: 16 · 2025: 18 · 2024: 16 · 2023: 18 · 2022: 12 · 2021: 16 · 2020: 10 · 2019: 4 · 2018: 4
FWCI: 8.10
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Current Medical Research and Opinion (publishedVersion)
PubMed (publishedVersion)
Topics: Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Reproductive Health and Contraception
Health Sciences › Medicine › Reproductive Medicine › Reproductive Health and Technologies
Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Keywords: ovulation prediction, calendar method, luteinizing hormone surge, menstrual cycle length, fertility awareness, rhythm method, Standard Days Method
MeSH terms: Data Accuracy, Calendars as Topic, Adult, Female, Humans, Menstrual Cycle, Ovulation, Predictive Value of Tests, Pregnancy, Prognosis, Natural Family Planning Methods, Fertile Period, Mobile Applications

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Can apps and calendar methods predict ovulation with accuracy?

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